Building the National Spatial Data Ecosystem through collaborative thinking – An interview with Attila Hülber

What are the most critical prerequisites for building a successful national spatial data ecosystem*?

The most important is regular engagement among all stakeholders across interministerial, market, and educational. The International Spatial Data Conference 2026 is the kick-off for that journey.

What makes cooperation successful in the geospatial sector?

The ultimate success factor is the ability of participants to leave their institutional roles behind. We need to pool our collective expertise and experience without merely defending our own organizations' interests. If we create a space for shared knowledge rather than a forum for interest groups, we participate not as delegates, but as invited contributors driving the national spatial data ecosystem forward. Success also requires compromise — the willingness to trade immediate individual advantages for the national good. In the long run, this actually benefits our own organizations, but it requires prioritizing the collective interest first. Look at the relationship between Google and Google Maps: although Google Maps is a subsidiary, its value to the ecosystem is immense. This synergy is built on mutual benefits, a model we can absolutely leverage locally.

What do you see as the biggest challenge in making geospatial data more accessible and widely reusable?

One major challenge is the misconception surrounding open data, which we need to clear up. Open data does not mean everything is free; it means the model is sustainable. Sustainability requires revenue, which is why we must offer premium, value-added services that robust, market-based actors are willing to pay for.There is room for everyone in the spatial data market. In fact, even with all current players combined, we barely have enough capacity to meet growing demands.

Globally, we see different models related to spatial data. Some countries produce highly refined data and sell it to companies like Google, which then build the services. The German model is different—they focus heavily on data sovereignty, keeping both data production and services under state control, even if a market actor could potentially handle certain tasks more efficiently. Then there is the hybrid model, which is closest to our approach: we provide data for free where it makes sense, but specialized, sector-specific datasets remain restricted.

How will AI shape the geospatial sector in the coming years?

Right now, AI in spatial data is like being on a scholarship — it is still in the learning phase. We cannot fully rely on it yet, and it is nowhere near replacing human professionals. In this stage, we actually need more experts than are currently available. While transport and mobility — the intersection of spatial data and AI— will likely be the main drivers, in the meantime AI is already leading the way in processing satellite imagery. Our focus leans more toward immobile spatial data, which will integrate these technologies further down the road.

What is the key message you would like to share and discuss with the audience in Budapest?

A critical buzzword is data gathering. Geospatial data is expensive, and acquiring it should be done deliberately and centrally, guided by a clear strategy. As for the services derived from this data — let’s co-create them. This conference is the perfect place to start that conversation.